So far, we've learned to design systems as a group of interacting objects, where each interaction is viewing the objects involved at an appropriate level of abstraction. But we don't know yet how to create those levels of abstraction. There are a variety of ways to do this; we'll discuss some advanced design patterns in Chapter 8 and Chapter 9. But even most design patterns rely on two basic principles known as composition and inheritance.
Composition is the act of collecting together several objects to compose a new one. Composition is usually a good choice when one object is part of another object. We've already seen a first hint of composition in the mechanic example. A car is composed of an engine, transmission, starter, headlights, and windshield, among numerous other parts. The engine, in turn, is composed of pistons, a crank shaft, and valves. In this example, composition is a good way to provide levels of abstraction. The car object can provide the interface required by a driver, while also providing access to its component parts, which offers a deeper level of abstraction suitable for a mechanic. Those component parts can, of course, be further broken down if the mechanic needs more information to diagnose a problem or tune the engine.
This is a common first example of composition, bit it's not a very good one when it comes to designing computer systems. Physical objects are easy to break into component objects. People have been doing it at least since the ancient Greeks originally postulated that atoms were the smallest unit of matter (they, of course, didn't have access to particle accelerators). Computer systems are generally less complicated than physical objects, yet identifying the component objects in such systems does not happen as naturally. The objects in an object-oriented system occasionally represent physical objects like people, books, or telephones. More often, however, they represent abstract ideas. People have names, books have titles, and telephones are used to make calls. Calls, titles, accounts, names, appointments, and payments are not usually considered objects in the physical world, but they are all frequently modeled components in computer systems.
Let's try modeling a more computer-oriented example to see composition in action. We'll be looking at the design of a computerized chess game. This was a very popular pastime among academics in the '80s and '90s. People were predicting that computers would one day be able to defeat a human chess master. When this happened in 1997 (IBM's Deep Blue defeated world chess champion, Gary Kasparov), interest in the problem waned, although there are still contests between computer and human chess players, and the program has not yet been written that can defeat a human chess master 100% of the time.
As a basic, high-level analysis: a game of chess is played between two players, using a chess set featuring a board containing sixty-four positions in an 8x8 grid. The board can have two sets of sixteen pieces that can be moved, in alternating turns by the two players in different ways. Each piece can take other pieces. The board will be required to draw itself on the computer screen after each turn.
I've identified some of the possible objects in the description using italics, and a few key methods using bold. This is a common first step in turning an object-oriented analysis into a design. At this point, to emphasize composition, we'll focus on the board, without worrying too much about the players or the different types of pieces.
Let's start at the highest level of abstraction possible. We have two players interacting with a chess set by taking turns making moves.
What is that? It doesn't quite look like our earlier class diagrams. That's because it isn't a class diagram! This is an object diagram, also called an instance diagram. It describes the system at a specific state in time, and is describing specific instances of objects, not the interaction between classes. Remember, both players are members of the same class, so the class diagram looks a little different:
The diagram shows that exactly two players can interact with one chess set. It also indicates that any one player can be playing with only one chess set at a time.
But we're discussing composition, not UML, so let's think about what the Chess Set is composed of. We don't care what the player is composed of at this time. We can assume that the player has a heart and brain, among other organs, but these are irrelevant to our model. Indeed, there is nothing stopping said player from being Deep Blue itself, which has neither a heart nor brain.
The chess set, then, is composed of a board and thirty-two pieces. The board is further comprised of sixty-four positions. You could argue that pieces are not part of the chess set because you could replace the pieces in a chess set with a different set of pieces. While this is unlikely or impossible in a computerized version of chess, it introduces us to aggregation. Aggregation is almost exactly like composition. The difference is that aggregate objects can exist independently. It would be impossible for a position to be associated with a different chess board, so we say the board is composed of positions. But the pieces, which might exist independently of the chess set, are said to be in an aggregate relationship with that set.
Another way to differentiate between aggregation and composition is to think about the lifespan of the object. If the composite (outside) object controls when the related (inside) objects are created and destroyed, composition is most suitable. If the related object is created independently of the composite object, or can outlast that object, an aggregate relationship makes more sense. Also keep in mind that composition is aggregation; aggregation is simply a more general form of composition. Any composite relationship is also an aggregate relationship, but not vice versa.
Let's describe our current chess set composition and add some attributes to the objects to hold the composite relationships:
The composition relationship is represented in UML as a solid diamond. The hollow diamond represents the aggregate relationship. You'll notice that the board and pieces are stored as part of the chess set in exactly the same way a reference to them is stored as an attribute on the chess set. This shows that once again, in practice, the distinction between aggregation and composition is often irrelevant once you get past the design stage. When implemented, they behave in much the same way. However, it can help to differentiate between the two when your team is discussing how the different objects interact. Often you can treat them as the same thing, but when you need to distinguish between them, it's great to know the difference (this is abstraction at work).
We have discussed three types of relationships between objects: association, composition, and aggregation. But we have not fully specified our chess set, and these tools don't seem to give us all the power we need. We discussed the possibility that a player might be a human or it might be a piece of software featuring artificial intelligence. It doesn't seem right to say that a Player is associated with a human, or that the artificial intelligence implementation is part of the Player object. What we really need is the ability to say that "Deep Blue is a player" or that "Gary Kasparov is a player".
The is a relationship is formed by inheritance. Inheritance is the most famous, well-known, and over-used relationship in object-oriented programming. Inheritance is sort of like a family tree. My grandfather's last name was Phillips and my father inherited that name. I inherited it from him (along with blue eyes and a penchant for writing). In object-oriented programming, instead of inheriting features and behaviors from a person, one class can inherit attributes and methods from another class.
For example, there are thirty-two chess pieces in our chess set, but there are only six different types of pieces (pawns, rooks, bishops, knights, king, and queen), each of which behaves differently when it is moved. All of these classes of piece have properties, like color and the chess set they are part of, but they also have unique shapes when drawn on the chess board, and make different moves. See how the six types of pieces can inherit from a Piece class:
The hollow arrows, of course, indicate that the individual classes of pieces inherit from the Piece class. All the subtypes automatically have a chess_set and color attribute inherited from the base class. Each piece provides a different shape property (to be drawn on the screen when rendering the board), and a different move method to move the piece to a new position on the board at each turn.
We actually know that all subclasses of the Piece class need to have a move method, otherwise when the board tries to move the piece it will get confused. It is possible we want to create a new version of the game of chess that has one additional piece (the wizard). Our current design would allow us to design this piece without giving it a move method. The board would then choke when it asked the piece to move itself.
We can implement this by creating a dummy move method on the Piece class. The subclasses can then override this method with a more specific implementation. The default implementation might, for example, pop up an error message that says, That piece cannot be moved. Overriding methods in subtypes allows very powerful object-oriented systems to be developed. For example, if we wanted to implement a player class with artificial intelligence, we might provide a calculate_move method that takes a Board object and decides which piece to move where. A very basic class might randomly choose a piece and direction and move it. We could then override this method in a subclass with the Deep Blue implementation. The first class would be suitable for play against a raw beginner, the latter would challenge a grand master. The important thing is that other methods on the class, such as the ones that inform the board as to which move was chosen would not need to be changed; this implementation can be shared between the two classes.
In the case of chess pieces, it doesn't really make sense to provide a default implementation of the move method. All we need to do is specify that the move method is required in any subclasses. This can be done by making Piece an abstract class with the move method declared abstract. Abstract methods basically say "We need this method in a subclass, but we are declining to specify an implementation in this class."
Indeed, it is possible to make a class that does not implement any methods at all. Such a class would simply tell us what the class should do, but provides absolutely no advice on how to do it. In object-oriented parlance, such classes are called interfaces.
Now it's time for another long buzzword. Polymorphism is the ability to treat a class differently depending on which subclass is implemented. We've already seen it in action with the pieces system we've described. If we took the design a bit further, we'd probably see that the Board object can accept a move from the player and call the move function on the piece. The board need not ever know what type of piece it is dealing with. All it has to do is call the move method and the proper subclass will take care of moving it as a Knight or a Pawn.
Polymorphism is pretty cool, but it is a word that is rarely used in Python programming. Python goes an extra step past allowing a subclass of an object to be treated like a parent class. A board implemented in Python could take any object that has a move method, whether it is a Bishop piece, a car, or a duck. When move is called, the Bishop will move diagonally on the board, the car will drive someplace, and the duck will swim or fly, depending on its mood.
This sort of polymorphism in Python is typically referred to as duck typing: "If it walks like a duck or swims like a duck, it's a duck". We don't care if it really is a duck (inheritance), only that it swims or walks. Geese and swans might easily be able to provide the duck-like behavior we are looking for. This allows future designers to create new types of birds without actually specifying an inheritance hierarchy for aquatic birds. It also allows them to create completely different drop-in behaviors that the original designers never planned for. For example, future designers might be able to make a walking, swimming penguin that works with the same interface without ever suggesting that penguins are ducks.
When we think of inheritance in our own family tree, we can see that we inherit features from more than just one parent. When strangers tell a proud mother that her son has, "his fathers eyes", she will typically respond along the lines of, "yes, but he got my nose".
Object-oriented design can also feature such multiple inheritance, which allows a subclass to inherit functionality from multiple parent classes. In practice, multiple inheritance can be tricky business, and some programming languages, (most notably, Java) strictly prohibit it. But multiple inheritance can have its uses. Most often, it can be used to create objects that have two distinct sets of behaviors. For example, an object designed to connect to a scanner and send a fax of the scanned document might be created by inheriting from two separate scanner and faxer objects.
As long as two classes have distinct interfaces, it is not normally harmful for a subclass to inherit from both of them. But it gets messy if we inherit from two classes that provide overlapping interfaces. For example, if we have a motorcycle class that has a move method, and a boat class also featuring a move method, and we want to merge them into the ultimate amphibious vehicle, how does the resulting class know what to do when we call move? At the design level, this needs to be explained, and at the implementation level, each programming language has different ways of deciding which parent class's method is called, or in what order.
Often, the best way to deal with it is to avoid it. If you have a design showing up like this, you're probably doing it wrong. Take a step back, analyze the system again, and see if you can remove the multiple inheritance relationship in favor of some other association or composite design.
Inheritance is a very powerful tool for extending behavior. It is also one of the most exciting advancements of object-oriented design over earlier paradigms. Therefore, it is often the first tool that object-oriented programmers reach for. However, it is important to recognize that owning a hammer does not turn screws into nails. Inheritance is the perfect solution for obvious is a relationships but it can be abused. Programmers often use inheritance to share code between two kinds of objects that are only distantly related, with no is a relationship in sight. While this is not necessarily a bad design, it is a terrific opportunity to ask just why they decided to design it that way, and if a different relationship or design pattern would have been more suitable.